Job Title : Associate Director, Epidemiology Analytics
Job Schedule : Hybrid is preferred - would consider a remote-based candidate - must be able to come in once a quarter.
RESPONSIBILITIES :
- Provide data management of diverse data (e.g., real-world setting and clinical trial) to set up epidemiologic data sets for various approaches, quantitative epidemiologic data analysis, interpretation of results, visualization of results, and generate manuscripts to disseminate findings.
- Conduct statistical analyses for epidemiological research and safety queries, including but not limited to :
- Descriptive summary and multivariable regression
- Exploratory analysis for safety endpoints in clinical trial data
- Setup and analysis of case-control and cohort study designs
- Signal detection analysis in spontaneous reports (e.g., FAERS, EVDAS)
- Signal detection / evaluation analysis in RWD
- Data mining (including free-text mining of unstructured data fields) using diverse data sources and methods
- Development of automation platform (e.g., R Shiny App) o Literature review and meta-analysis
- Collaborate with cross-functional teams to evaluate and manage adverse events and risks associated with pharmaceutical products.
- Participate in cross-functional meetings and provide input and guidance as needed.
- Participate in the preparation and submission of regulatory documents related to drug safety.
- Maintain and manage project plans to provide deliverables on time.
- Collaborate with global epidemiology teams to ensure consistency and quality in safety reporting and processes.
- Maintain compliance with all applicable regulations and guidelines related to pharmacovigilance and drug safety.
- Stay informed about emerging safety issues and contribute to the development of risk management strategies
- Mentor and provide guidance to junior team members.
Skills :
Experience in epidemiologic methods and data analysis (pharmaceutical industry in safety or associated service provider experience is preferred)Proficiency with programming in R, SAS, or Python for data mining and epidemiologic analysisStrong written, oral and electronic communication skillsExcellent leadership skills, with the ability to work effectively in a collaborative team environmentThe ideal candidate will have a strong background in both biostatistics and epidemiology (or other medical fields)Education :
Master's degree (with 7+ years of experience) or PhD (with 4+ years of experience) in Biostatistics, Data Science, Statistics, Applied Mathematics, Epidemiology or related field